1. Field of the Invention
The present invention relates to a method of detecting a frequency characteristic, and more particularly, to a method of more precisely processing an image signal by analyzing the frequency distribution of the signal and using the analysis result in a signal processing block to reduce noise in the signal or improve details of the signal.
2. Description of the Related Art
FIG. 1 illustrates a conventional noise reduction device set on a filtering frequency band. If the device is a high-pass filter, only highfrequency components of a signal are allowed to pass through the filter and other components are filtered. If the device is a band-pass filter, only frequencies within a particular frequency band are allowed to pass through the filter. If the device is a low-pass filter, only low-frequency components are allowed to pass through the filter.
FIG. 2 illustrates a conventional detail enhancement device. The conventional detail enhancement device is also set on a filtering frequency band. As above, the device may be a high-pass filter, a band-pass filter, or a low-pass filter. The detail enhancement device makes components which cannot be perceived by the human eyes look sharper by amplifying a filtered signal and lapping the filtered signal over the original signal.
FIG. 3 is a table illustrating the maximum frequency, sampling frequency, and Nyquist frequency of a pixel of different types of input images. Referring to FIG. 3, the maximum frequency is 4.3 Mhz when an input image is a standard definition (SD) image, i.e., the resolution is 720×480 which is the same as that of an image generated using the National Television System Committee (NTSC) standard or the phase alternation line (PAL) standard. Sampling is the process of making a discontinuous pulse train by cutting a continuous wave signal by predetermined intervals of time. Here, the predetermined interval of time is called sampling frequency. As is well known, the sampling frequency is two times greater than the maximum frequency component of a signal. This is because frequency folding occurring at a frequency component greater than the sampling frequency/2 causes aliasing. The sampling frequency/2 is called the Nyquist frequency. Referring to FIG. 3, the sampling frequency of the input SD image is 13.5 Mhz and the Nyquist frequency is 6.75 Mhz.
When the input image is a high-definition (HD) image, i.e., the resolution of the input image is 1920×1080, the maximum frequency is 30 Mhz. In this case, the sampling frequency is 74.25 Mhz and the Nyquist frequency is 37.125 Mhz.
If an SD image of 720×480, which has the maximum frequency of 4.3 Mhz, is up scaled to an HD image of 1920×1080, the maximum frequency of the pixels of the up-scaled HD image in the horizontal direction is 8.87 Mhz, i.e., (4.3/6.75)×(720/1920)×37.125=8.87 Mhz.
That is, if an image is up scaled or down scaled, the maximum frequency of the pixels of the scaled image is determined by resolution and frequency ratios.
FIG. 4 illustrates waveform diagrams of signals passing through a conventional high-pass filter. When an input image signal having a waveform 41 passes through a high-pass filter with a filtering frequency band 42, a signal having a waveform 43 is output from the filter. However, when an up-scaled image signal having a waveform 44 is filtered by the high-pass filter having the filtering frequency band 42, since a cutoff frequency is much higher than the scale ratio of the up-scaled image, data output from the filter is not reliable. For instance, if the scaled signal having the waveform 44 is a signal that is scaled to the double of the original signal, no image signal is output from the high-pass filter with the filtering frequency band 42, the cutoff frequency of which is π/2, when the scaled signal passes through the high-pass filter. Therefore, it is impossible to reduce noise in the signal or enhance the details of the signal.
There are various types of image signals including SD image signals and HD image signals. Also, as different types of image processors are developed, scaling is frequently required to adjust the resolution of an image signal to match an image processor. For instance, in order to reproduce an SD image in an HD-TV, the SD image needs to be up scaled so that its resolution is adjusted to be equivalent to that of the HD-TV. As described above, when the up-scaled image is processed using a high-pass filter whose cutoff frequency is much higher the scale ratio of the image as explained with reference to FIG. 4, the filtering operation is not successfully performed, and thus data output from the filter is not reliable. Further, the absence of reliable data results in a failure to reduce noise in an image signal or enhancing the details thereof using the conventional filter.